Guang Lin Honored with Early Career Achievement Award

Congratulations to Guang Lin, a computational mathematics researcher at Pacific Northwest National Laboratory, on being selected to receive the Laboratory Director's 2012 Ronald L. Brodzinski Award for Early Career Exceptional Achievement. He was recognized for his leading research in uncertainty quantification and petascale data analytics applied to climate models.

PNNL's annual Science and Engineering Achievement Awards recognize distinguished staff who have made notable contributions to the scientific or engineering communities.

Guang is a member of PNNL's Computational Mathematics group where he focuses on research in high-order numerical methods for stochastic partial differential equations, uncertainty quantification, computational fluid dynamics, petascale data analysis and dimensional reduction techniques, extreme-scale computing, and multiscale modeling.

He is the principal investigator on two projects funded by the Department of Energy's Office of Advanced Scientific Computing Research (ASCR). One ASCR project focuses on extracting and reducing data from massive volumes of information to quantify and reduce the uncertainty in the climate models. He also led another ASCR project on developing scalable uncertainty quantification and multiscale algorithms for modeling high-dimensional stochastic multiscale complex systems with application to uncertainty quantification of carbon sequestration and multiscale material predictive modeling.

Currently, he leads uncertainty quantification projects under both the multi-lab Carbon Capture Simulation Initiative and the PNNL Carbon Sequestration Initiative to develop an uncertainty quantification and risk assessment pipeline to efficiently quantify the uncertainty in carbon capture and sequestration simulations.